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@ckinsey
ckinsey / chain.py
Last active Aug 19, 2018
Chain.py Builds the Markov Models from Slack
View chain.py
import json
import markovify
import re
import time
from slackclient import SlackClient
BOT_TOKEN = "insert bot token here"
@nikitakit
nikitakit / tf_beam_decoder.py
Last active Aug 16, 2019
Tensorflow Beam Search
View tf_beam_decoder.py
"""
Beam decoder for tensorflow
Sample usage:
```
from tf_beam_decoder import beam_decoder
decoded_sparse, decoded_logprobs = beam_decoder(
cell=cell,
@monikkinom
monikkinom / rnn-lstm.py
Last active Sep 3, 2019
Tensorflow RNN-LSTM implementation to count number of set bits in a binary string
View rnn-lstm.py
#Source code with the blog post at http://monik.in/a-noobs-guide-to-implementing-rnn-lstm-using-tensorflow/
import numpy as np
import random
from random import shuffle
import tensorflow as tf
# from tensorflow.models.rnn import rnn_cell
# from tensorflow.models.rnn import rnn
NUM_EXAMPLES = 10000
@wangruohui
wangruohui / Install NVIDIA Driver and CUDA.md
Last active Oct 16, 2019
Install NVIDIA Driver and CUDA on Ubuntu / CentOS / Fedora Linux OS
View Install NVIDIA Driver and CUDA.md
@off99555
off99555 / Machine Learning Curriculum.md
Last active Apr 29, 2019
Machine learning resources and related artificial intelligence concepts.
View Machine Learning Curriculum.md
@danijar
danijar / blog_tensorflow_variable_sequence_labelling.py
Last active Jun 15, 2019
TensorFlow Variable-Length Sequence Labelling
View blog_tensorflow_variable_sequence_labelling.py
# Working example for my blog post at:
# http://danijar.com/variable-sequence-lengths-in-tensorflow/
import functools
import sets
import tensorflow as tf
from tensorflow.models.rnn import rnn_cell
from tensorflow.models.rnn import rnn
def lazy_property(function):
@application2000
application2000 / how-to-install-latest-gcc-on-ubuntu-lts.txt
Last active Oct 13, 2019
How to install latest gcc on Ubuntu LTS (12.04, 14.04, 16.04)
View how-to-install-latest-gcc-on-ubuntu-lts.txt
These commands are based on a askubuntu answer http://askubuntu.com/a/581497
To install gcc-6 (gcc-6.1.1), I had to do more stuff as shown below.
USE THOSE COMMANDS AT YOUR OWN RISK. I SHALL NOT BE RESPONSIBLE FOR ANYTHING.
ABSOLUTELY NO WARRANTY.
If you are still reading let's carry on with the code.
sudo apt-get update && \
sudo apt-get install build-essential software-properties-common -y && \
sudo add-apt-repository ppa:ubuntu-toolchain-r/test -y && \
@danijar
danijar / blog_tensorflow_sequence_classification.py
Last active Apr 29, 2019
TensorFlow Sequence Classification
View blog_tensorflow_sequence_classification.py
# Example for my blog post at:
# https://danijar.com/introduction-to-recurrent-networks-in-tensorflow/
import functools
import sets
import tensorflow as tf
def lazy_property(function):
attribute = '_' + function.__name__
View blog_tensorflow_scope_decorator.py
# Working example for my blog post at:
# https://danijar.github.io/structuring-your-tensorflow-models
import functools
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
def doublewrap(function):
"""
A decorator decorator, allowing to use the decorator to be used without
@arundasan91
arundasan91 / CaffeInstallation.md
Created Apr 2, 2016
Caffe Installation Tutorial for beginners
View CaffeInstallation.md

Caffe

Freshly brewed !

With the availability of huge amount of data for research and powerfull machines to run your code on, Machine Learning and Neural Networks is gaining their foot again and impacting us more than ever in our everyday lives. With huge players like Google opensourcing part of their Machine Learning systems like the TensorFlow software library for numerical computation, there are many options for someone interested in starting off with Machine Learning/Neural Nets to choose from. Caffe, a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and its contributors, comes to the play with a fresh cup of coffee.

Installation Instructions (Ubuntu 14 Trusty)

The following section is divided in to two parts. Caffe's documentation suggest

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